If there’s a history of alcoholism in the family, you have a higher risk of developing AUD. However, knowing your family history of addiction shouldn’t make you feel hopeless, as if you’re bound to the same fate. Aside from risk factors, there are also positive “protective” factors that make a person less susceptible to alcohol addiction. This suggests that while a family history of alcoholism can increase susceptibility, it doesn’t dictate destiny. These insights suggest that those with a genetic predisposition to alcoholism could benefit from early interventions and tailored treatments. There has been limited knowledge of the molecular genetic underpinnings of addiction until now.
Supplementary Data 36
Some promising results are emerging from GWAS studies; however, larger sample sizes are needed to improve GWAS results and resolution. As the field of genetics is rapidly developing, whole genome sequencing could soon become the new standard of interrogation of the genes and neurobiological pathways which contribute to the complex phenotype of AUD. Linkage studies are limited in terms of their spatial resolution, and thus, association studies that measure differences in allele frequencies between ‘case’ and ‘control’ populations were also pursued. Early association https://ecosoberhouse.com/ studies focused on a limited number of variants in or near genes selected a priori for their biological relevance to the trait of interest or physical location in the genome informed by prior linkage results. These inconsistent findings have tempered expectations and investment in both linkage and candidate gene studies. Alcoholism is known to be moderately heritable yet the search for genetic vulnerability factors has proven to be more difficult than originally thought and to date only a small proportion of the genetic variance has been accounted for.
PAU PRS for phenome-wide associations
Your socioeconomic status is made up of economic and societal factors such as your income, level of education, employment, location of residence, and available resources. Having a close family relative, such as a parent, can account for up to 60% of your risk of developing AUD. Alcohol use disorder (AUD) can have a hereditary component, but not everyone living with AUD has a family history of AUD. MVP is a biobank supported by the United States Department of VA with rich phenotypic data collected using questionnaires and the VA electronic health record system.
Linking risk genes to brain chromatin interaction
- People with enzyme variants that allow for the fast buildup of acetaldehyde from alcohol (ethanol) are at less risk for addiction compared to those who metabolize alcohol efficiently to acetate.
- Overview of genetically informed designs that have been used or are proposed for use in the COGA sample.
- Cross-ancestry fine mapping improved the identification of potential causal variants, and cross-ancestry PRS analysis was a better predictor of alcohol-related traits in an independent sample than single-ancestry PRS.
This finding suggests that variants of a gene or genes within this region reduced the risk of becoming alcoholic. ADH alleles are known to affect the risk for alcoholism; however, the known protective alleles occur at high frequency in Asian populations but are rare in the Caucasian population that makes up most of the COGA sample (Edenberg 2000). Therefore, these analyses may have identified a new protective ADH allele or another protective gene located nearby.
- The sharing of data and biospecimens has been a cornerstone of the COGA project, and COGA is a key contributor to large-scale GWAS consortia.
- A subsequent COGA scan found strong linkage of resting EEG beta power, an intermediate phenotype for alcoholism, to the same chromosome 4 region [43].
- Parallel to the emphasis on increasing sample sizes to drive gene discovery is the growing recognition of the value of a sample like COGA with its family‐based design, deep phenotyping, longitudinal framework, multi‐modal data, wide age range, and ancestral diversity (see, Figure 2 for summary of key contributions enabled by COGA).
- Published today in Nature Mental Health, the study was led by researchers at the Washington University in St. Louis, along with more than 150 coauthors from around the world.
- Thus it is not surprising that diseases of the GI system,including cirrhosis, pancreatitis, and cancers of the upper GI tract are affected byalcohol consumption80-86.
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Given this genetic similarity, if heredity plays a significant role in alcoholism, identical twins should exhibit a pronounced concordance rate. In genetics, the concordance rate signifies the likelihood of two individuals with similar genes manifesting the same condition. An experiment using rats at Linköping University in Sweden discovered that those with reduced expression of the gene GAT-3 become addicted to alcohol. According to the 2022 National Survey on Drug Use and Health (NSDUH), 15.1 million people in the US suffer from alcohol use disorder (AUD). This encompasses issues often referred to as alcohol dependence, alcohol misuse, alcohol addiction, and even the oft-used term—alcoholism. Phenotypic data were collected from MVP participants using questionnaires and the VA EHR and a blood sample was obtained for genetic analysis.
Genetic Influences on Alcohol Metabolism
Two of these genes are the dopamine D2 receptor gene (DRD2) and a serotonin transporter gene (HTT). However, the analyses found no evidence that DRD2 affected the risk for alcoholism (Edenberg et al. 1998a) or that HTT was linked to either alcoholism in general or to a more severe form of alcoholism (Edenberg et al. 1998b). One study used a staged meta-analysis to explore comorbid alcoholand nicotine dependence and detected genome-wide evidence of association withSNPs spanning a region on chromosome 5 that includes both IPO11(importin 11) and HTR1A (5-hydroxytryptamine (serotonin)receptor 1A, G protein-coupled)78.
Paul A. Slesinger
As more variants are analysed and studies are combined for meta-analysis to achieve increased sample sizes, an improved picture of the many genes and pathways that affect the risk of alcoholism will be possible. These included mean age-adjusted AUDIT-C scores, which are more stable than measures at a single point in time (more likely reflecting traits rather than states) and contrast with meta-analytic studies that may use phenotypes reflecting the lowest-common denominator among the studies comprising the sample. However, our analyses were limited by our reliance on the AUDIT-C, which includes only the first 3 of the 10 AUDIT genetics of alcoholism items. We also obtained cumulative AUD diagnoses, which are also more informative than assessments obtained at a single time point. Because the diagnosis of AUD is based on features other than alcohol consumption per se2,5, use of the AUD diagnosis from the EHR augmented the information provided by the AUDIT-C phenotype. Although EHR diagnostic data are heterogeneous, large-scale biobanks such as the MVP yield greater statistical power to link genes to health-related traits repeatedly documented over time in the EHR than can ordinarily be achieved in prospective studies23, justifying the lower resolution of EHR data.